Journal of Human Kinetics volume 43/2014, 97-104 DOI: 10.2478/hukin-2014-0094 97

Physical Activity, Sport & Health

1 - Integrated Colleges of Northern Minas Gerais – Funorte, Brazil. 2 - University of Tras-os-Montes and Alto Douro, Vila Real, Portugal. 3 - University President Antônio Carlos - UNIPAC, Uberlândia, MG, Brazil. 4 - Fire Department of the State of Minas Gerais, 5th Battalion Fire Department, Uberlândia, MG, Brazil. 5 - University Center Triangle - UNITRI, Uberlândia, MG, Brazil.

.

Authors submitted their contribution to the article to the editorial board.

Accepted for printing in the Journal of Human Kinetics vol. 43/2014 on November 2014.

 Nutritional Status Associated with Metabolic Syndrome

in Middle-School Children

in the City of Montes Claros - MG, Brazil

by

Igor Raineh Durães Cruz1,2, Daniella Mota Mourão1,2, Daniel Antunes Freitas1,

Andrey George Silva Souza1,2, Alessandra Ribeiro Pereira1,2, Felipe José Aidar2,3,4,5,

André Luiz Gomes Carneiro2,3

The aim of this study was to investigate the association between nutritional status and prevalence of metabolic

syndrome (MS) in middle-school students in the city of Montes Claros - MG. The sample consisted of 382 students,

aged 10-16 years. Nutritional status was evaluated using the Body Mass Index (BMI). Metabolic syndrome (MS) was

defined as the presence of two or more criteria in accordance with definition of the International Diabetes Federation.

The overall prevalence of MS was 7.9%. 9.7% of students with MS were overweight and 72.4% were obese. Therefore,

it can be inferred that carrying excess weight considerably increases the chances for a child to develop MS, and

concomitantly increases the child’s risk for developing cardiovascular disease.

Key words: dyslipidemia, metabolic syndrome, children, cross-sectional study, youth.

Introduction Metabolic syndrome (MS) is defined by

the presence of risk factors such as high blood

pressure, abdominal obesity,

hypertriglyceridemia, low concentration of high

density lipoprotein (HDL-c) and hyperglycemia

(Eckel et al., 2005; Oda, 2012; Chiu et al., 2012).

Prevalence of MS has increased among children,

adolescents and adults, and is closely related to

the presence of excess weight or obesity (Cruz

and Goran, 2004; Zimmet et al., 2007).

No consensus has been reached in the

literature regarding the diagnosis of MS in

pediatric populations because blood pressure

(BP), lipid profile and anthropometric values vary

with age and maturity, requiring different cutoff

points to account for variations in age, sex and

other criteria (Damiani et al., 2011). However, the

International Diabetes Federation (IDF) has

established criteria for identifying SM in children

and teenagers, dividing them into three groups: 6

to < 10 years old, 10 to 16 years old and > 16 years

old (Zimmet et al., 2007; Damiani et al., 2011). In

accordance with the criteria of the IDF, MS is a

combination of abdominal obesity and one or

more other risk factors (Zimmet et al., 2007).

Studies using the cutoff points established

by the IDF indicate the presence of MS in 16.3% of

children living in Malaysia (Zimmet et al., 2007),

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4.6% of adolescents in Vietnam (Nguyen et al.,

2011), 33% in Turkey (Sagun et al., 2011), and

39.7% of a municipal population in Brazil (Costa

et al., 2012).

Investigations of various methodologies

concur that MS is associated with cardiovascular

diseases (CVD) regardless of age, and that excess

weight or obesity is the most prevalent risk factor

(Cobayashi et al., 2010; Armas et al., 2012). Thus,

as the incidence of childhood obesity is rising, the

prevalence of MS in this population is also

increasing (Pacífico et al., 2011) and needs to be

futher investigated in the Brazilian pediatric

population (Silva et al., 2012; Stabelini et al., 2012).

The aim of this study was to investigate

the association between nutritional status and

prevalence of metabolic syndrome in middle-

school children in the city of Montes Claros, MG,

Brazil.

Material and Methods

The sample was determined in two stages:

1) stratification of elementary school students (n =

53.032) and middle school students (n = 15.505),

and 2) clustering of schools according to the four

regions of the city: north (n = 10), south (n = 17),

east (n = 15), west (n = 13), totaling 55 schools.

Four schools (one from each region) were

randomly drawn in order to minimize the

logistical difficulties of displacement while

acquiring a sufficient number of students to

constitute the sample. At each of these randomly

selected schools, all students between the ages of

10 and 16 years old who participated in physical

education classes were invited to take part in the

study. The calculation of the final sample was

established with a margin of error of three

percentage points and a confidence level of 95%, a

design effect of 1.5 plus 10% for possible losses

and / or refusals. Thus, 421 children were selected

using the formula: n = (ZZ).p.q.N/e.e.(N-1)+

p.q.Z.Z, where Z = confidence interval, P =

probability of being rejected 50%, q = probability

of being chosen, 50% N= population and e =

percentage of error ≤ 0.05 (Almeida and Freire,

2003; Cruz et al., 2014).

Of the 421 students initially selected, 15

students (12 boys and 3 girls) did not obtain the

signature of a parent or guardian on the consent

form; 4 children (3 boys and 1 girl) did not

properly complete the questionnaire; 12 students

(3 boys and 9 girls) did not complete the physical

examination; and 8 male students were randomly

excluded, reaching the final sample of 382

students distributed in the following regions:

north (n = 62), south (n = 111), east (n = 105) and

west (n = 104).

Informed consent to participate in the

study was signed by a parent or guardian of every

student included in the results of the study. The

study was approved by the Institutional Review

Board of the State University of Montes Claros

(process no. 152.330/12). Participants were duly

informed about the study and signed informed

consent forms in accordance with Resolution

196/1996 of the Brazilian National Health Council,

and in accordance with the ethical principles

contained in the Declaration of Helsinki (1964,

revised in 1975, 1983, 1989, 1996 and 2000).

Instruments

Socioeconomic status (CSE) of

participants in the sample was attained by means

of a structured questionnaire which took into

account the educational background of parents,

skin color of the children and family income.

Based on this information, participants were

classified into eight groups (A1, A2, B1, B2, C1, C2,

D, E) and these eight groups were assigned to one

of two categories of economic status: high

economic status (A1, A2, B1) or low socioeconomic

status (B2, C1, C2, D and E) (Fernandes et al., 2008).

Variables of nutritional status and metabolic

syndrome

Anthropometry: Body mass (BM) and

height (H) were measured on a medical platform

scale (Filizola, Brazil) with a weight capacity of

150 kg with precision to 100 g and a height

capacity of 2 m with precision to 0.1 cm. The

subject stood with his or her arms along the body

and with his or her head positioned in the

Frankfurt plane. Nutritional status was defined by

the Body Mass Index (BMI) and classified as

normal weight, overweight or obesity (Cole et al.,

2000). Abdominal circumference (AC) was

measured using a flexible metal anthropometric

tape (Sanny SN 40-10, Brazil). The measurements

were performed upon exhalation with the values

on the measurement tape facing the evaluator and

were determined in the horizontal plane. Males

were evaluated at the plane just below the last rib

and females evaluated at the level of the navel

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(Lohman et al., 1998).

Blood pressure (SBP / DBP) - was measured using a

sphygmomanometer (BD, Brazil) and a Rappaport

stethoscope (Premium, Brazil) that was previously

tested and calibrated. The evaluation took place

with the individual in a sitting position after 10

min of rest. The right arm supported at the heart

level was used for the analysis. The first Korotkoff

sound was considered for systolic blood pressure

reading and the last for diastolic blood pressure.

A five minute rest interval was given between the

first and subsequent measurement. The average of

the two measurements was calculated to

minimize measurement biases (BGH, 2010).

Blood samples - blood samples for the biochemical

tests were collected at Santa Clara Laboratory

(Montes Claros, MG, Brazil) through

venipuncture with disposable needles and

syringes, with participants fasting for 12 hours.

Approximately 10 ml of blood was collected in a

test tube without anticoagulants. The test tubes

were labeled with identification tags and stored in

two coolers (®Termolar, Brazil) with a capacity of

200 tubes each. The tubes were placed in a

centrifuge at 3500 rpm for 10 min and stored in a

refrigerator at -20 ° C for later analysis. The

concentrations of triglycerides (TG), high density

cholesterol (HDL-C) and glucose (GLU) were

determined by a calorimetric oxidase enzyme

analyzer provided by Liquiform Diagnostic Kits ®

(Labtest, Brazil).

The International Diabetes Federation (IDF)

created age appropriate definitions and

approaches to the treatment of SM for children

and teenagers, dividing them into groups: 6 to <

10 years, 10 to 16 years and > 16 years. The IDF

recommends that the diagnosis of MS should not

be given to children under the age of 10,

recommending that the child should be counseled

about the need for weight loss and a change of

lifestyle. However, at 10 years or older, the

diagnosis should be given and should be based on

the presence of abdominal obesity and the

presence of two or more of the following

syndromes: TG> 150 mg / dL, HDL <40 mg / dL,

Glu> 100 mg / dL, SBP ≥ 130 and DBP ≥ 85 mmHg

20. For adolescents above the age of 16, the adult

criteria are used (Damiani et al., 2011).

Procedures

The subjects were evaluated by two

physical education teachers with a minimum

experience of 30 ratings. The Pearson values for

intra-rater and inter-rater reliability were 0.975

and 0.967, respectively. Data collection occurred

in four stages. In the first stage, the researcher

presented the objectives of the project to the

directors of the randomly selected schools. The

school directors subsequently informed the

physical education teachers about the study

procedures. Individual participants were

randomly drawn from the population of students

who fulfilled the criteria for inclusion in the

sample. In the second stage, the researcher

presented the randomly selected students with

the informed consent form to be completed by a

parent or guardian and returned the next day. In

the third stage, questionnaires were applied and

anthropometric measurements were completed.

In the fourth stage, the students came to the

laboratory for blood sampling after fasting for 12

hours. The time between each step was a

minimum interval of 24 hours.

Statistics

The Statistical Package for Social Sciences

(SPSS 20.0 for Windows ®) was used to analyze

the data. Descriptive statistics were done through

measures of central tendency mean ± standard

deviation (M ± SD). We applied the chi-square test

in order to associate prevalence of MS with

nutritional status. The magnitude was calculated

from the odds ratio (OR) with confidence

intervals of 95% (95% CI).

Results

Table 1 shows the description of the

sample, categorized by nutritional status.

33.3% of male participants and 66.7% of

female participants were found to be overweight

and 34.5% of male participants and 65.5% of

female participants were found to be obese.

Students under the age of 13 were most affected

by being overweight or obese. BM was greater

among obese children. There were more

overweight and obese children in the elementary

school than in the middle school. Low income

status was associated with children being

overweight or obese.

Table 2 describes the criteria for diagnosis

of MS, categorized by nutritional status.

The results show that being overweight

corresponded with abnormal (greater than

recommended) waist circumference (WC) in

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12.5% of participants and other abnormal values,

increasing the chances of diagnosis of MS, since

the IDF uses the criterion of change in waist

circumference combined with two criteria.

Table 1

Description of the sample categorized by nutritional status. VARIABLES Nutricional Status Total

Normal weight Overweight Obese

Gender

Male 117 (41,6%) 24 (33,3%) 10 (34,5%) 151 (39,5%)

Female 164 (58,4%) 48 (66,7%) 19 (65,5%) 231 (60,5%)

Age

<13 121 (43,1%) 36 (50%) 16 (55,2%) 173 (45,3%)

≥13 160 (56,9%) 36 (50%) 13 (44,8%) 209 (54,7%)

Weight (kg) 44,44 ± 9,63 59,45 ± 10,83 72,79 ± 13,64 49,42 ± 13,51

Height (m) 1,55 ± 0,1 1,57 ± 0,09 1,54 ± 0,93 1,55 ± 0,1

Education

1 st grade/ Elementary school 234 (83,3%) 67 (93,1%) 26 (89,7%) 327 (85,6%)

2 nd grade/High school 47 (16,7%) 5 (6,9%) 3 (10,3%) 55 (14,4%)

Race

Non-white 233 (82,9%) 60 (83,3%) 26 (89,7%) 319 (83,5%)

White 48 (17,1%) 12 (16,7%) 3 (10,3%) 63 (16,5%)

Socio-economic status

HSS 27 (9,6%) 8 (11,1%) 2 (6,9%) 37 (9,7%)

LSS 254 (90,4%) 64 (88,9%) 27 (93,1%) 345 (90,3%)

HSS: High Socioeconomic Status; LSS: Low Socioeconomic Status.

Table 2

Description of MS criteria met according to nutritional status. Variables Nutritional Status

p Normal Overweight Obesity OR CI (95%)

WC (cm)

Normal 281 (100%) 63 (87,5%) 9 (31%)

Abnormal -- 9 (12,5%) 20 (69%) 15,55 (5,43-44,51) 0,000*

SBP (mmHg)

Normal 281 (100%) 72 (100%) 27 (93,1%)

Abnormal -- -- 2 (6,9%) 3,66 (2,65-5,05) 0,024*

DBP (mmHg)

Normal 281 (100%) 72 (100%) 28 (96,6%)

Abnormal -- -- 1 (3,4%) 3,57 (2,6-4,89) 0,113

TG (mg/dL)

Normal 279 (99,3%) 70 (97,2%) 24 (82,8%)

Abnormal 2 (0,7%) 2 (2,8%) 5 (17,2%) 7,29 (1,32-40,07) 0,01*

HDL-c (mg/dL)

Normal 240 (85,4%) 56 (77,8%) 19 (65,5%)

Abnormal 41 (14,6%) 16 (22,2%) 10 (34,5%) 1,84 (0,71-4,74) 0,202

GLU (mg/dL)

Normal 278 (98,9%) 72 (100%) 27 (93,1%)

Abnormal 3 (1,1%) -- 2 (6,9%) 3,66 (2,65-5,058) 0,024*

OR: odds ratio, CI: confidence interval. p: statistical significance from the chi-square test.

CA: waist circumference, SBP: systolic blood pressure, DBP: diastolic blood pressure,

TG: triglycerides, HDL-C: High Density Cholesterol, GLU: glucose.

*p<0,05

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Table 3

Description of prevalence (%) of MS with 95% confidence, according to nutritional status. Variables Nutritional Status

p Normal Overweight Obesity OR CI (95%)

Metabolic

Syndrome

Absent 279 (99,3%) 65 (90,3%) 8 (27,6%)

Present 2 (0,7%) 7 (9,7%) 21 (72,4%) 24,37 (7,89-75,25) 0,000*

OR: odds ratio, CI: confidence interval. p: statistical significance from the chi-square test.

*p<0,05

Students with obesity had a greater

tendency towards abnormal values for the WC

(OR = 15.55, CI: 5.43 to 44.51, p = 0.001), SBP (OR =

3.66, CI: 2, 65 to 5.05, p = 0.024), TG (OR = 7.29, CI:

1.32 to 40.07, p = 0.01) and GLU (OR = 3.66, CI:

2.65 -5.058, p = 0.024). The differences in risk

factors between obese and normal weight children

were significant, revealing a strong association

between obesity and metabolic syndrome.

Table 3 describes prevalence of MS and its

association with the nutritional status of

schoolchildren in the city of Montes Claros.

The overall prevalence of MS was 7.9% in

the sample of school children. However, only

0.7% of normal weight children and 9.7% of

overweight children had MS, while 72.4% of obese

children fulfilled the criteria for diagnosis of MS.

This significant association (p = 0.001)

demonstrates that the obese children were 24.37

times more likely to meet the criteria for diagnosis

of MS (CI: 7.89 to 75.25).

Discussion

The aim of this study was to investigate

the association between nutritional status and

prevalence of metabolic syndrome (MS) in

middle-school children. The data from this study

showed higher prevalence of excess weight or

obesity among female students, indicating that

girls are more likely to develop MS than boys.

This corresponds to a similar study of 5913

participants in the United States in which females

had a higher frequency of being overweight or

obese when compared to males (Maty et al., 2008).

The relative values of height and weight

are considered in the calculation of the BMI. In

this way, a more comprehensive view considers

that both height and age need to be considered

when evaluating whether a child is overweight or

obese. When a child is heavy for their height and

age, slow and steady weight loss are

recommended to reduce the BMI and minimize

cardiovascular risk (Terres et al., 2006; Kassi et al.,

2011).

In several studies it has been noted that

education reduces or eliminates certain risk

factors. For example, one study showed a

significant negative association between lower

levels of education and excess weight or obesity.

This study relates that when parents have only

five to eight years of schooling, the risk of their

children being overweight or obese is 2.53 (CI:

1.32 to 4.85) times higher than amongst children

whose parents have at least a high school

education (Terres et al., 2006). Another study

found that children tended to lose excess weight

during high school when they were exposed to

nutritional knowledge and tools to control weight

(Barrington et al., 2010).

The present study found that non-white

and low income children had higher incidences of

being overweight or obese. Since non-white status

is associated with lower incomes in Brazil, the

similarity in these associations are related (Ribeiro

et al., 2009). Similarly, a longitudinal study

conducted with 29,146 Americans between 2 to 17

years showed more excess weight among black

and Hispanic when compared with white

children. The association between racial identity

and nutritional status is considered to be a by-

product of unequal educational and vocational

opportunities and cultural differences (Freedman

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et al., 2006). Numerous studies have associated

lower socioeconomic status with obesity,

hypertension and dyslipidemia (Kassi et al., 2011;

Ribeiro et al., 2009).

Similar studies support a relationship

between increased (abnormal) waist

circumference (WC) and prevalence of children

being overweight (12.5%) or obese (69%) and

demonstrate that a high level of abdominal fat in

childhood is related to insulin resistance,

dyslipidemia and hypertension (Johnson et al.,

2010). A recent study conducted in 991 schools in

Paraná, Brazil showed that female students had a

tendency toward abnormally high values for

waist circumference and that this was related to

the intake of excess sugar, limited physical

inactivity, unhealthy family life styles and low

socioeconomic status (Moraes et al., 2013).

BMI and WC are widely used as

predictors of nutritional status, but the IDF also

uses blood pressure as an essential criterion for

diagnosis of MS (Reaven, 2006). Individuals with

high BMI tend to have 3.6 and 2.7 times the risk of

change in SBP and DBP, respectively (Ribeiro et

al., 2006). Studies have demonstrated that

elevated BP in childhood and adolescence is

associated with anthropometric changes and a

higher incidence of MS in adulthood (Ribeiro et

al., 2006).

High concentrations of triglycerides

present a picture of hypertriglyceridemia, which

contributes to decreases in HDL-C and the

production of LDL cholesterol particles. These

changes result in an atherogenic lipoprotein

profile congruent with an increased risk of

cardiovascular disease (Moraes and Falcão, 2013;

Reaven, 2006; Benmohammed et al., 2011). A case-

control study of adolescents living in Malaysia

indicated that being overweight or obese affects

the odds of having high triglycerides by 12% and

similarly resulted in a 2.5 times greater chance of

developing MS (Costa et al., 2012).

Hyperglycemia was detected in 6.9% of

children with obesity. It is possible that this

relatively low prevalence could be inaccurate as

the study did not investigate the use of

hypeglycemic or diabetic medications among

children in the sample. The IDF emphasizes the

importance of measuring the fasting glucose as it

is a more accurate measure of risk for MS

(Zimmet et al., 2007). Another study suggests that

hyperglycemia may not be concurrent with MS as

it may occur later, when the function of the

pancreas is challenged because of ongoing efforts

to keep normal glucose levels through increased

insulin production (Ferrannini and Iozzo, 2006).

While it is not advisable to use glucose levels as a

sole indicator of MS since studies of this

relationship present a wide variety of criteria, the

existent literature uniformly supports the

presence of a positive association between

increased glucose levels and higher prevalence of

being overweight or obese (Moraes and Falcão,

2013; Papoutsakis et al., 2012).

In our study, 0.7% of normal weight, 9.7%

of overweight and 72.4% of obese children met the

criteria for MS, indicating that nutritional status

plays a key role in its incidence. A case-control

study with 402 children living in Malaysia found

prevalence of MS of 16.3% among obese children

and 5.3% among overweight children (Wee et al.,

2011). Similarly, the relationship between MS and

nutritional status was investigated in 693 high

school students, finding prevalence of 4.6% and

11.8% among overweight and obese adolescents

(Cobayashi et al., 2012). Our findings are also in

agreement with the results of a cross-sectional

survey conducted with 133 subjects of an

endocrinology clinic that indicated the influence

of obesity on the occurrence of MS, pointing out

that one in five obese patients met three or more

criteria for diagnosis of MS (Nguyen et al., 2010).

In research conducted with hospitalized children

and adolescents with leukemia in Saudia Arabia,

MS was diagnosed in 7.1% of the total sample

with higher incidences among overweight and

obese subjects (Aldhafiri et al., 2012).

An important limitation of the present

study was that as a cross-sectional study, it was

only capable of describing the current status of

the participating children and adolescents and,

therefore, it was not capable of illuminating the

causes and consequences of the problem

Conclusion

In conclusion, nutritional status tends to

be associated with MS among school children,

with prevalence of 0.7% for normal weight

students, 9.7% for overweight students and 72.4%

for obese students in the study population,

leading to the conclusion that obese participants

were 24.37 times more likely to be diagnosed with

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MS, which implies a much higher degree of risk

for cardiovascular disease.

Practical Applications

This study confirmed an association

between metabolic syndrome (MS) and being

overweight or obese amongst school children in

Montes Claros, Brazil. This indicates a great need

for effective educational programs that promote

an increase in physical activity and education in

good nutrition. MS can be avoided by the

adaption of better physical education programs in

school, afterschool and on the weekends. This

study indicates a need for public policies that

incorporate health education in public

programming and quality public and private

education. A mere 30 minutes of physical activity

three times a week could make a significant

difference in the incidence of overweight and

obese children, and, subsequently, reduce the risk

of developing Metabolic Syndrome and

consequent cardiovascular diseases.

References

Aldhafiri F, Al-Nasser A, Al-Sugair A, Al-Mutairi H, Young D, Reilly JJ. Obesity and Metabolic Syndrome in

Adolescent Survivors of Standard Risk Childhood Acute Lymphoblastic Leukemia in Saudi Arabia.

Pediatr Blood Cancer, 2012; 59: 133-137

Almeida LS, Freire T. Methodology of Research in Educational Psychology. Braga: Lusografe, 33-39; 2003

Armas MGG, Megías SM, Viveros MM, Bolaños PI, Piñero BV. Prevalence of metabolic syndrome in a

population of obese children and adolescents. Endocrinología y Nutrición, 2012; 59: 155-159

Barrington DS, Baquero MC1, Borrell LN, Crawford ND. Racial/Ethnic Disparities in Obesity Among US-

born and Foreign-born Adults by Sex and Education. Obesity, 2010; 18: 422-424

Benmohammed K, Nguyen MT, Khensal S, Valensi V, Lezzar A. Arterial hypertension in over weight and

obese Algerian adolescents: Role of abdominal adiposity. Diabetes & Metabolism, 2011; 37: 291-297

Chiu TY, Chen CY, Chen SY, Soon CC, Chen JW. Indicators associated with coronary atherosclerosis in

metabolic syndrome. Clinical Chem Acta, 2012; 413: 226-231

Cobayashi F, Oliveira FLC, Escrivão MAMS, Silveira D, Taddei JAAC. Obesity and cardiovascular risk

factors in adolescents from public schools. Braz Arch Cardiol, 2010; 95: 200-206

Cole TJ, Bellizzi MC, Flegal KM, Dietz WH. Establishing a standard definition for child overweight and

obesity worldwide: international survey. BMJ, 2000; 320: 1241-1243

Costa RF, Santos NS, Goldraich NP, Barski TF, Andrade KS, Kruel LFM. Metabolic syndrome in obese

adolescents: a comparison of three different diagnostic criteria. J Pediatr, 2012; 88: 303-309

Cruz IRD, Freitas DA, Soares WD, Mourão DM, Aidar JF, Carneiro ALG. Metabolic Syndrome and its

association with socio-economic level in students. Rev. CEFAC, 2014; 16: 1294-1301

Cruz ML, Goran MI. The Metabolic Syndrome in Children and Adolescents. Current Diabetes Reports, 2004; 4:

53-62

Damiani D, Kuba VM, Cominato L, Damiani D, Dichtchekenian V, Menezes Filho HC. Metabolic syndrome

in children and adolescents: questions on terminology, but not in cardiometabolic risk. Braz Arch

Endocrinol Metab, 2011; 55: 576-582

Eckel RH, Grundy SM, Zimmet PZ. The metabolic syndrome. Lancet, 2005; 365: 1415-1428

Fernandes AM, Casonatto J, Destro-Christófaro DG, Ronque ERV, Oliveira AR, Freitas Junior IF. Risk for

overweight among adolescents from different socioeconomic classes. Braz J Medical Assoc, 2008; 54:

334-336

Ferrannini E, Iozzo P. Is insulin resistance atherogenic? A review of the evidence. Atheroscler Suppl, 2006; 7:

5-10

Freedman DS, Khan LK, Serdula MK, Ogden CL, Dietz WH. Racial and ethnic differences in secular trends

for childhood BMI, weight, and height. Obesity, 2006; 14: 301-308

Johnson ST, Kuk JL, Mackenzie KA, Huang TT-K, Rosychuk RJ, Ball GDC. Metabolic Risk Varies According

Brought to you by | Universidade de Trás-os-MontesAuthenticated

Download Date | 1/15/15 6:02 PM

104   Nutritional status associated with metabolic syndrome in middle-school children 

Journal of Human Kinetics - volume 43/2014 http://www.johk.pl 

to Waist Circumference Measurement Site in Overweight Boys and Girls. J Pediatr, 2010; 156: 247-252

Kassi E, Pervanidou P, Kaltsas G, Chrousos G. Metabolic syndrome: definitions and controversies. BMC

Medicine, 2011; 9: 48-51

Lohman TG, Roche AF, Martorell R. (Eds.) Antropometric standardization reference manual. Champaign, IL.

Human Kinetics Publishers; 1988

Maty SC, Lynch JW, Raghunathan TE, Kaplan GA. Childhood Socioeconomic Position, Gender, Adult Body

Mass Index, and Incidence of Type 2 Diabetes Mellitus Over 34 Years in the Alameda County Study.

Am J Public Health, 2008; 98: 1486-1494

Moraes ACF de, Falcão MC. Lifestyle factors and socioeconomic variables associated with abdominal obesity

in Brazilian adolescents. Annals of Human Biology, 2013; 40: 1-8

Nguyen THHD, Tang HK, Kelly P, Ploeg HP Van der, J Dibley MJ. Association between physical activity

and metabolic syndrome: a cross sectional survey in adolescents in Ho Chi Minh City, Vietnam. BMC

Public Health, 2010; 10: 141-146

Oda E. Metabolic syndrome: its history, mechanisms, and limitations. Acta Diabetol, 2012; 49: 89-95

Pacífico L, Anania C, Martino F, Poggiogalle E, Chiarelli F, Arca M. Management of metabolic syndrome in

children and adolescents. Nutrition Metabol Cardio Diseases, 2011; 21: 455-466

Papoutsakis C, Yannakoulia M, Ntalla I, Dedoussis GV. Metabolic syndrome in a Mediterranean pediatric

cohort: prevalence using International Diabetes Federation–derived criteria and associations with

adiponectin and leptin. Metabolism Clinical and Experimental, 2012; 61: 140-145

Reaven GM. The metabolic syndrome: is this diagnosis necessary? Am J Clin Nutr, 2006; 83: 1237-1247

Ribeiro RQC, Lotufo PA, Lamounier JA, Oliveira RG, Soares JF, Botter DA. Additional cardiovascular risk

factors associated with overweight in children and adolescents: the study of the heart of Belo

Horizonte. Braz Arch Cardiol, 2006; 86: 408-418

Ribeiro RR, Santos KD, Guerra-Júnior G, Barros-Filho AA. Nutritional status of schoolchildren blacks and

whites in southern Brazil. Braz J Medical Assoc, 2009; 55: 121-126

Sangun Ö, Dündar B, Köflker M, Pirgon Ö, Dündar N. Prevalence of metabolic syndrome in obese children

and adolescents using three different criteria and evaluation of risk factors. J Clin Res Ped Endo, 2011; 3:

70-76

Silva DAS, Pelegrini A, Silva AF da, Grigollo LR, Petroski EL. Abdominal obesity and associated factors in

adolescents: comparison of two different Brazilian regions economically. Braz Arch Endocrinol Metab,

2012; 56: 291-299

Stabelini Neto A, Bozza R, Ulbrich A, Mascarenhas LPG, Boguszewski MCS, Campos W. Metabolic

syndrome in adolescents of different nutritional status. Braz Arch Endocrinol Metab, 2012; 56: 104-109

Terres NG, Pinheiro RT, Horta BL, Pinheiro KAT, Horta LL. Prevalence and factors associated with

overweight and obesity in adolescents. Braz J Public Health, 2006; 40: 627-633

VI Brazilian Guidelines on Hypertension (BGH). Braz J Hypertension, 2010; 17: 11-17

Wee BS, Bee K, Poh BK, Bulgiba A, Ismail MN, Ruzita AT, Hills AP. Risk of metabolic syndrome among

children living in metropolitan Kuala Lumpur: A case control study. BMC Public Health, 2011; 11: 333-

340

Zimmet P, Alberti KGMM, Kaufman F, Tajima N, Silink M, Arslanian S, Wong G, Bennett P, Shaw J, Caprio

S. The metabolic syndrome in children and adolescents – an IDF consensus report. Pediatric Diabetes,

2007; 8: 299-306

Corresponding author:

Igor Raineh Durães Cruz

Integrated Colleges of Northern Minas Gerais – Funorte, Brazil - Rua Geovane Soares Cruz 93, Lourdes –

cep: 39401482 – Montes Claros, MG, Brazil.

Phone number: +55 38 91638230; E-mail: igorrainneh@hotmail.com

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